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MCP Compras.gov.br

compras_fornecedor_cnpj_receita

Read-onlyIdempotent

Dados públicos do CNPJ na Receita Federal (via BrasilAPI/MinhaReceita).

Retorna razão social, nome fantasia, situação cadastral, CNAE primário e secundários, QSA (sócios), capital social, natureza jurídica, porte, endereço e datas de início de atividade e da situação cadastral.

Quando usar: complemento do compras_perfil_fornecedor_completo para due diligence (avaliar porte, sócios, CNAEs vs objeto da licitação). Os dados são da Receita; este MCP não consulta sanções aqui — para isso use as tools de sanção (CEIS/CNEP/CEPIM/CEAF).

Cache 24h. Em caso de 404 ou erro upstream, retorna encontrado=false com diagnóstico em _erro em vez de propagar exception.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cnpjYesCNPJ a consultar (14 dígitos, com ou sem pontuação). Usa BrasilAPI por padrão; trocável via env `CNPJ_PROVIDER=minhareceita`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and idempotentHint annotations, the description discloses additional behavior: 24h cache, provider configurable via environment variable, and that it returns 'encontrado=false' with a diagnostic error instead of throwing exceptions. This adds meaningful transparency about edge cases and operational details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with clear sections (what it returns, when to use, what it does not do). It is informative without being verbose, and each sentence adds value—no filler or redundant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the data returned, the use case, exclusions (sanctions), caching, error handling, and provider configuration. It is contextually rich and provides enough information for an agent to decide when and how to invoke the tool, especially given the output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'cnpj' is fully documented in the schema: format (14 digits, with or without punctuation), provider selection (BrasilAPI default, minhareceita via env). The description in the schema covers the parameter completely, and the main description reinforces its purpose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool's function (public CNPJ data from Receita Federal) and enumerates the returned fields (razão social, CNAEs, QSA, etc.). It also differentiates from sibling tools by positioning itself as a complement to compras_perfil_fornecedor_completo and clarifying that it does not cover sanctions, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'Quando usar' section provides explicit guidance: use for due diligence, and explicitly directs to sanction tools (CEIS/CNEP/CEPIM/CEAF) when sanctions are needed. It also mentions cache and error behavior, giving clear conditions for its use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.6/5.0
Disambiguation3/5

Most tools target distinct resources, and descriptions are extremely detailed, often explicitly warning about look-alikes. However, there is real overlap between composite and single-purpose tools (e.g., compras_checar_sancoes_fornecedor vs compras_perfil_fornecedor_completo vs compras_sancao_*), and similar-looking pairs like compras_contratos_consultar vs compras_contrato_comprasnet_consultar or compras_arp_listar vs compras_pncp_atas_listar require careful reading. With 100 tools, an agent will still face meaningful selection ambiguity.

Naming Consistency3/5

The dominant pattern is snake_case with a compras_ prefix, but the order and style vary: some are domain-first (compras_catmat_buscar), some are verb-first (compras_buscar_contratacoes_similares), and some are bare entity names with no verb (compras_sancao_ceis, compras_pncp_modalidades). The many listar/consultar/buscar variants are readable, but the convention is not predictable enough for a 100-tool surface.

Tool Count1/5

100 tools is an extreme count for any MCP server, regardless of domain breadth. Even if each tool has a legitimate upstream endpoint, this volume will heavily tax context windows and make reliable tool selection harder. Many tools could be consolidated into parameterized families (e.g., contratos, sancoes, pncp resources).

Completeness4/5

The server covers the Brazilian procurement domain remarkably well: catalogs, ARPs, 14.133 contracts, legacy regime, price research, suppliers, sanctions, PGC/PCA, PNCP, and Comprasnet contract subresources. Minor gaps remain, such as listing a supplier's full contract history without specifying an órgão, and some upstream limitations are only papered over with client-side workarounds.